I have 3 groups of data. Group 1 contains 11 values, group 2 contains 7 and group 3 contains 11 values. The values are in the form of 'percentage change over time'.

I would like to test to see if the groups averages are statistically different from one another. It seems like Chi-squared would work but the data is continuous. Any help would be greatly appreciated.


It seems that your analysis is more amenable to ANOVA 1-way. You want to test equality of means against the alternative that at least one group has a different mean.

Assuming approximate normality of the data (but ANOVA is quite robust against non-normality), independence of observations and same variances (a much more critical assumption), this would be a simple ANOVA analysis, were it not because the data is unbalanced (not same number of observations per group).

You can work around this using a simple regression model such as $$ y_{ij} = \beta_i + \epsilon_{ij}$$ where $y_{ij}$ is the $j$-th observation in the $i$-th group and testing $H_0: \beta_1 = \beta_2 = \beta_3$ agains the alternative that at least one is different from the rest.

  • $\begingroup$ Thank you very much for your help - could I just ask how I would go about carrying out that type of regression? Would I do the regression then the ANOVA? $\endgroup$ – NAR Jul 20 '18 at 8:47
  • $\begingroup$ No, you just perform the regression and test equality of the three coefficients $\beta_1$, $\beta_2$ and $\beta_3$. $\endgroup$ – F. Tusell Jul 20 '18 at 9:03

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.